# scryer-mcp

> Use this tool when you need to synchronize architecture models with code or modify existing models to reflect intent. It enables AI agents to read, modify, and build from models, ensuring the model remains the source of truth. Ideal for use cases where consistency between design and implementation is crucial, such as software development or system integration projects.

Canonical page: https://skillsregistry.net/skills/aklos-scryer  
JSON: https://api.skillsregistry.net/v1/skills/aklos-scryer

## Description

Enables AI agents to read, modify, and build from architecture models, keeping the model as the source of truth for intent and synchronized with code.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/seyjrzgsq7)
- **Repository:** <https://github.com/aklos/scryer>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "aklos-scryer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aklos-scryer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aklos-scryer/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt